Method and apparatus for real time enhancing of the operation of a fluid transport pipeline

ABSTRACT

A real time method and dynamic logic-based system for enhancing the operation of a pipeline network is disclosed. The system and method perform monitoring of the operation of a pipeline network, generate alarms in response to differing levels of destabilized pipeline operations, manage the generation of alarms based upon known operating events and operating conditions, diagnose potential source of the detected destabilized events and manage the operation of the pipeline.

CROSS REFERENCE TO RELATED PATENT APPLICATION

This application is a continuation of U.S. patent application Ser. No. 12/492,564, filed on Jun. 26, 2009, which relates and claims priority to U.S. Provisional Patent Application No. 61/129,466, filed on Jun. 27, 2008, entitled “A Method and Apparatus for Enhancing the Operation of a Fluid Transport Pipeline.”

FIELD OF THE INVENTION

The present invention relates to a method and system for enhancing the operation of a pipeline. In particular, the present invention is directed to a real time method and a dynamic, logic-based system for monitoring the operation of a pipeline network, generating alarms in response to differing levels of destabilized pipeline operations and managing the operation of the pipeline in response to the same. In particular, the present invention relates to a method and a dynamic behavior based system for the monitoring of a pipeline, and the detection and reporting of destabilized operating events including but not limited to possible pipeline rupture events based upon sensed hydraulic reactions within the pipeline network. The present invention also relates to a method and system for monitoring the generation of alarms in response to sensed destabilizing events. The present invention also relates to a system for maintaining the stable operation of the pipeline, monitoring potential destabilizing events and pinpointing the location of the same in order to enact sufficient remedial measures to avoid or prevent a catastrophic destabilized event (e.g., leak, rupture or equipment failure). The present invention also relates to a method and system for diagnosing destabilizing events.

BACKGROUND OF THE INVENTION

Pipelines are used to efficiently transport fluid commodities from one location to another and, generally, span long distances. Pipelines are typically monitored and controlled to ensure the integrity of the pipeline. This is normally accomplished from a central control center where equipment settings and measured parameters are monitored and controlled. Leaks can be detected by measuring various parameters, particularly flow rate and pressure. This monitoring depends on calculating the mass of the contents of the pipe (fluid), and observing over a period of time whether the contents of the pipe changes in a manner indicative of fluid leaving the pipe at an unmeasured location, perhaps through a rupture in the pipeline. The effect of a leak on the measured parameters and thus on the calculated mass of fluid within the pipe is mathematically relatable to the mass of fluid which is leaving the pipe through the rupture. Using existing methods, large ruptures can be detected in relatively short periods of time. Small ruptures, however, if at all detectable, require longer periods of time to accumulate the necessary volumetric discrepancies to indicate excessive system measurement imbalance, which may result in a greater amount of fluid leaking from the system into the surrounding environment. These systems depend on a balancing algorithm to determine if fluid is leaving the pipeline at an un-metered location to determine if there is a rupture. As may be appreciated, these prior art systems require that a sufficient volume of fluid has left the pipeline through the rupture before detection of the rupture can occur. This can result in a significant environmental impact in the area surrounding the rupture as inferential measurement systems are commonplace and relatively lethargic with respect to hydraulic wavespeeds and the ensuing segmental decompressions that follow rupture events in closed pressurized hydraulic networks.

Calculating the mass of the contents in the pipe is subject to many inaccuracies (e.g., errors in measurement of the mass of the fluid entering and leaving the pipe, inaccurate knowledge of the changes in the physical space within the pipe due to temperature fluctuations in the pipeline walls and the minimal knowledge of the actual temperatures and pressures within the pipeline, transducer calibration and/or configuration correctness).

The approximate location of a piping rupture can be determined using existing methods for large ruptures by examining the effects of the rupture on the flow rate and pressure at locations where measurements are available. Locating the rupture under existing methods is subject to several possible inaccuracies related to measurement system and ancillary instrumentation system parameterization, configuration, and calibration. As the volume of fluid exiting through the rupture drops to a small fraction of the flow rate of the pipeline, the effect of the missing fluid will drop below the accuracy with which the parameters used to calculate the location are measured. Additionally, common inferential mass metering systems often operate within nonlinear regions of equipment operation thus degrading leak detecting capabilities.

There is a need for a system and method to rapidly detect and accurately predict the location of a destabilizing event in a pipeline network. Others have attempted to develop systems that are more effective in identifying ruptures than those described above, but these systems only identify leaks and ruptures and not destabilizing events. These destabilizing events may not be a leak or rupture, but impact the operation of the pipeline. These systems, however, compare sensed conditions with pre-identified stored leak profiles. These systems do not identify unstable operations that are not leaks or ruptures, the locations of these unstable operations or the source(s) of concern. These systems are not dynamic, as such, these systems do not adequately respond to abnormal changes in the operation of a pipeline network that are not indicative of the presence of a leak or a rupture.

U.S. Pat. No. 5,361,622 to Wall discloses a device and method for the detection of leaks in a pipeline. Wall utilizes a transducer for measuring instantaneous pipeline pressure. Wall utilizes a computer to compare rates of change of the measured pressure at successive preselected and fixed timed intervals at isolated nodes. The computer compares the measured rate of change with a preselected total change in a specified characteristic at that node. When the measured rate of change exceeds the preselected maximum total change, an alarm is triggered indicating the possibility of a leak or rupture. These maximums, however, do not vary or adjust for variations in the pipeline operation. Wall does not aid in the determining the location of the leak or rupture because its analysis is site specific. Wall provides for local or isolated analysis at select points within the pipeline. Wall does not corroborate these changes with any changes occurring at other nodes. This lack of corroboration leads to a greater potential for false alarms.

U.S. Pat. No. 5,388,445 to Walters et al discloses a method and an apparatus for detecting a wave front caused by the onset of leaks or other transient events in a pipeline. Walters seeks to detect a significant wave front traveling in the high noise environment characteristic of pipelines, and to accurately measure its amplitude and time of arrival. Walters discloses detecting a wave front indicative of a transient event occurring in a pipeline by measuring a characteristic related to pressure of a fluid in the pipeline with a measuring device positioned at a given point on the pipeline, and outputting analog signals proportional to the pressure. The detection of the wave front arrival time may be used directly to sound an alarm. The amplitude may be used to find the location and/or size of the leak. Walters, however, does not provide means for discounting (i) external influences on the pipeline, which may produce wave fronts but are not leaks or (ii) internal influences such as changes in the viscosity or strip operations within the pipeline, which again may produce wave fronts but are not leaks. The model employed in Walters is a fixed model. It does not adjust or learn based upon varying pipeline operations and external influences; rather, it relies upon a fixed reference event to determine leaks. Accordingly, the system disclosed by Walters may be prone to false leak indications. Furthermore, Walters looks at measurements Obtained during affixed time window and does not account for events that may start during one window and end during another window. Accordingly, the system may fail to detect a leak nor does it attempt to identify or diagnose destabilizing events that are not leaks but that may adversely affect the pipeline network's efficiency of operation or safety.

U.S. Pat. No. 5,428,989 to Jerde et al discloses a method and an apparatus for detecting and characterizing a leak using a pressure transient. Jerde provides a plurality of pressure monitoring stations spaced along a pipeline at known distances from each other. The stations generate an arrival time signal when a pressure wave front is detected. The system can determine whether the arrival time signals from the plurality of monitoring stations correspond to the same event.

U.S. Pat. No. 6,389,881 and U.S. Pat. No. 6,668,619 both to Yang et al disclose an acoustic based method and apparatus for detecting and locating leaks in a pipeline. Yang utilizes a system for detecting leaks using the acoustic signal generated from a leak event in a pipeline. The system requires the use of non-industry standard specialized components mounted to the pipeline at selected locations. A pattern match filter is used to reduce false alarm rate and improve leak location accuracy by comparing acoustic waves generated by a leak with stored previously recorded signature leak profiles. Yang utilizes a time stamp of the acoustic signal to pinpoint the location of the leak. The system listens for acoustic waves to determine whether or not a leak is present. Normal operating events (such as pump start ups, etc.) and isolated events (such as a piece of equipment hitting the pipeline) may generate an acoustic signal that travels through the pipeline but not a pressure wave characteristic of a teak. As such, the Yang system is more prone to issuing false alarms.

U.S. Pat. No. 6,970,808 to Abhulimen et al discloses a method for detecting and locating leaks in a pipeline network in real-time utilizing a flow model that characterizes flow behavior for at least one of steady and unsteady states, which corresponding to an absence and a presence of model leaks in the pipeline network. A deterministic model is provided to evaluate at least one of a leak status and a no leak status relating to the pipeline network using deterministic criteria.

These prior art systems are not proactive systems; rather, these systems are reactive in nature retying upon comparisons to historical data or predetermined modeled results in order to determine whether or not a leak is present. These prior art systems essentially reset to the original threshold after each detection of a potential leak. The thresholds of prior art do not rescale themselves in real time to take into account normal changes in pipeline operation. The thresholds are generally high, which overlook changes due to small leaks. These prior art systems do not rely upon present pipeline activity in order to determine the presence of a leak or rupture, which may require further action nor do they perform corroborating steps to confirm a destabilized event, nor do they diagnose the source of the destabilizing event (e.g., process error, equipment malfunction). These systems do not continuously adjust detection thresholds to account for the various normal operating modes of pipeline networks. While it is desirable to maintain a stable pressure and stable flow through the pipeline network, changes in pressure and flow are common due to changes in viscosity of the various fluids flowing through the network, equipment malfunction, etc. These prior art systems are not capable of accounting for these variations in pipeline activity. As such, these prior art systems may generate a significant number of alarms indicating a potential leak. Each of these alarms requires some form of action by a pipeline operator. There is a need for a dynamic logic-based system that accurately responds to the varying operating conditions present in a pipeline network while accurately identifying destabilizing events including leaks and ruptures while minimizing false alarm events. Furthermore, there is a need for a system that effectively manages the generation of alarms.

SUMMARY OF THE INVENTION

It is an aspect of the present invention to provide a method and dynamic system of monitoring a pipeline network to identify possible destabilizing events in the pipeline network. The present invention is intended for use in various pipeline networks and is not intended to be limited to those networks used for transporting oil, liquefied natural gas, gas or products derived from the same. The method and associated system are contemplated for use in pipeline networks including but not limited to networks interconnecting one or more of the following: refineries, petrochemical production facilities, pumping stations, storage facilities, distribution terminals, drilling stations, off-shore terminals and offshore drilling platforms. It is contemplated the present invention has application in any environment where a liquid or other fluid is transported via pipeline (e.g., water distribution system, food processing facilities, etc).

The method according to an aspect of the present invention may include sensing one or more pressure waves within the pipeline network at predetermined locations within the pipeline network, and determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves. The destabilizing events can vary from a leak or rupture of the pipeline to a component failure in the field (e.g., a pump or valve or other pipeline equipment related to the operation of the pipeline) to a process error, which may attributed to an operator error (e.g., set point misplacement of a control valve or variable frequency drive adjustment) or misoperation of the pipeline. The destabilized events have varying degree of severity (with a potential leak or rupture having the highest level of severity). Nonetheless, each destabilizing event requires some level of attention. If a low level destabilizing event continues without implementing remedial measures steps, the efficient operation of the pipeline may be impacted, resulting in a potential fail safe operation (e.g., insufficient fluid feed to a pipeline pump, pressure within the pipeline is too high, component failure, etc.) By implementing corrective measures to stabilize the destabilizing event, potential ruptures and leaks can be prevented, stable operation is maintained, efficient pipeline operation is returned, damage to equipment is prevented and pipeline life may be extended (through reductions in strain, fatigue and wear on the pipeline).

In accordance with an aspect of the present invention, the sensing of pressure waves within the pipeline network occurs at the highest sampling rate permitted or sample rate limit of the pressure transmitter sensor associated with the pipeline. The sampling is accomplished using existing pipeline equipment and does not require the placement of additional or customized equipment on the pipeline for purposes of event detection. The sampling is repeated in order to determine the presence of a destabilizing event in the pipeline network. Determining the presence of a possible destabilizing event in the pipeline network in response to the sensing of the pressure waves may include detecting variations in the sensed pressure waves. This may include the use of the SCADA system to determine whether rapid pressure decay and the subsequential segmental decompression characteristic of leak events on a pressurized hydraulic network occurred within the pipeline system. The method preferably includes determining whether or not the detected variation exceeds an accepted standard deviation. Unlike prior art systems, the use as applied within the present invention of the standard deviation takes into account varying modes of pipeline operation (e.g., draw mode, where pipeline fluid is pushed from one end to the other but is also withdrawn at intermediate points, and tight line mode, where no pipeline fluid is withdrawn at intermediate points, etc.). The prior art systems rely upon a fixed threshold. When the threshold is exceeded, an alarm is triggered. According to an aspect of the present invention, the threshold utilized changes to account for changes in the operating conditions due to changes in operating mode, changes in operation due to normal noise, temperature, different types of fluids (e.g., gasoline or diesel fuels) and location of the pipeline (e.g., above ground, below ground, underwater). The threshold may be increased or decreased in response to known operating conditions or events. For example, the threshold may be increased in response to the startup or shutdown of a pump or other pipeline equipment. Increasing the threshold prevents the identification of an operationally acceptable destabilizing event that may be solely attributable to the component startup. When a pump shuts down, and steady state is reattained, the threshold may be decreased or retuned from transient noise to steady state normal noise thereby more tightly monitoring the system for operationally unacceptable destabilizing events. This would allow the detection of destabilizing events that may not have been identified if the threshold was maintained constant. Using the standard deviation, the reported high speed pressure decay can be analyzed to determine if it originated from known pipeline operational activities or is attributable to a potential leak or other destabilizing event. The presence of a high speed pressure decay is indicative of a leak or rupture. In the event that the pipeline is submerged underwater, there may be an increase in pressure as opposed to a pressure decay due to the pressure exerted on the pipeline from the water entering the pipeline. A comparison of the time of reported pressure reactions with the times of recent pipeline operational activities is made to determine if given the time differential and linear pipeline distance between the activity and the detection of the pressure response was caused by the normal pipeline activity by comparing time, speed, and distance calculations against known pipeline parameters and fluid wave propagating characteristics. The sensed pressure pulse for a destabilizing event moves faster through the pipeline than the normal flow profile of the fluid within the network.

In accordance with another aspect of the present invention, the method of monitoring the pipeline network may further comprise determining the location of the possible destabilizing event in the pipeline network in response to the sensed pressure waves. The presence and location of the possible destabilizing event may be reported to one or more operators of the pipeline network. In the event the destabilizing event is of a high level, the operator takes appropriate remedial measures (e.g., pump shutdown, setpoint adjustment, valve operation, system shutdown) to minimize the loss of fluid from the system and minimize the impact to the surrounding environment. Determining the location of a possible destabilizing event in the pipeline network in response to the sensed pressure waves may include identifying which predetermined locations a destabilizing event (e.g., a rupture) indicating pressure reaction is sensed at a first sensing time, then identifying which predetermined locations the sensed pressure wave is sensed at a second sensing time, and determining the location of a possible destabilizing event based upon the location of the sensed pressure wave at the first sensing time and the second sensing time. The plurality of coincidentally timed pressure reactions are analyzed to determine a probable location of the incident which caused the pressure reaction. The sensed reactions' chronology is compared for reasonableness against known parameters of the subject pipeline system and the fluid or fluid set within the pipeline.

In accordance with another aspect of the present invention, the method of monitoring a pipeline network may further include determining the certainty of the possible destabilizing event and reporting the presence, location and certainty of the possible destabilizing event to one or more operators of the pipeline network. The certainty of the possible destabilizing event may include comparing the determination of a possible destabilizing event based upon sensed pressure waves with one or more current sensed pipeline network operating conditions.

It is another aspect of the present invention to provide a system for monitoring a pipeline network for detecting destabilizing events in the same. The pipeline network may include a first facility, a second facility, at least one pipeline segment connecting the first facility and the second facility such that the fluid can flow between the first facility and the second facility, and at least one pumping station (which may include a pump set) connected to the at least one pipeline segment. Various facilities are contemplated to be within the scope of the present invention including but not limited to refineries, petrochemical production facilities, pumping stations, storage facilities, distribution terminals, drilling stations, and off-shore drilling platforms. For example, the pipeline may extend from a refinery to a distribution terminal, an off-shore drilling platform or terminal to on-shore storage or processing facilities or refinery. The network is not limited to two facilities. Various combinations and numbers of facilities and pipeline segments are considered to be within the scope of the present invention. Each pumping station preferably includes at least one pump. The pumping stations may include a centrifugal type pump or pump set for withdrawing fluid at the desired pressure and rate from the upstream pipeline segment and pushing the fluid into the downstream pipeline segment at the desired pressure and rate. The monitoring system includes a plurality of pressure sensing devices for sensing the presence of one or more pressure waves within the pipeline network. Each pressure sensor device is preferably an existing pressure transmitter associated with the pipeline. The plurality of pressure sensing devices preferably includes a pair of pressure sensing devices for each pumping station. A first sensing device of the pair of pressure sensing devices is located on one side of the pump or pump set and a second sensing device of the pair of pressure sensing devices is located on an opposite side of the pump or pump set. Each pressure sensing device is capable of sensing one or more pressure waves within the pipeline network. The monitoring system further includes a plurality of remote monitoring devices operatively connected to the first facility, the second facility and at least one pumping station. The remote monitoring devices monitor the operation of the pipeline network and collect operating data of the pipeline network from the sensing devices and other monitoring devices. Each of the plurality of pressure sensing devices is operatively connected to at least one remote monitoring device. The monitoring system further includes a control unit operatively connected to the plurality of remote monitoring devices for controlling the operation of the pipeline network based upon signals received from the plurality of remote monitoring devices. The control unit detects the presence of possible destabilizing events in the pipeline network and determines the location of possible destabilizing events in the pipeline network based upon the sensed pressure waves. This application is performed by a high speed time-synchronized array of pressure sensing field located instruments and processors.

The control unit includes a real time optimizer. The real time optimizer determines the presence of a destabilizing event in the pipeline network based upon the sensed pressure waves. Furthermore, the real time optimizer determines whether or not variations in the sensed pressure waves are present and whether or not each variation or variation set exceeds an accepted standard deviation (with respect to empirically determined normal pipeline system behavior for the current mode) or other statistical comparator (e.g., positive or negative rate of change of decompression in the network). The real time optimizer may further corroborate and determine the certainty of the possible destabilizing event by comparing the determination of a possible destabilizing event based upon sensed pressure waves with one or more sensed pipeline network operating conditions sensed by the plurality of remote monitoring devices. The real time optimizer determines the location of the destabilizing event in the pipeline network based upon the location of the pressure sensing devices that sensed a pressure wave of a particular reaction and the actual real-time pipeline system hydraulic character with respect to the empirically determined acceptable hydraulic profile.

The control unit may identify remedial measures to address the destabilizing event including but not limited to the modification of operating parameters, the resetting of equipment, notifying the human pipeline controller, and/or the maintenance review of equipment in response to the determination that a destabilization event exists. In the event that a rupture or leak is detected the control unit may identify or automatically execute remedial measures to minimize fluid loss from the system. The remedial measures may include but are not limited to the powering off of pumps to reduce flow to the leak, temporarily shutting down the pipeline, diverting the flow within the pipeline, and isolating the leak site.

It is another aspect of the present invention to provide a system that effectively provides for alarm management to reduce the number of the false alarms. During normal operation of the pipeline network, various steady-state and transient pressure profiles are generated that are not attributable to a destabilizing event, but nonetheless create pressure activity that generates an alarm signal. These can be attributed to normal pipeline operation and can be indicative of changes in operating mode and/or changes in operating events. For example, changing the operating mode from tight line mode to draw mode may create a pressure wave within the network giving rise to an alarm. Similarly, the normal operation of pumping units within the network (i.e., turning pumps on, off or adjusting a variable frequency drive) may create a pressure wave within the network giving rise to an alarm. These pressure waves reflect normal pipeline operation but may give rise to hundreds of false alarms on a daily basis. The dynamic nature of the system in accordance with the present invention provides effective alarm management to reduce the overall occurrence of the false alarms. This reduction in false alarms provides the pipeline operator with more time to address and respond to actual alarms as well as heighten the operator's sensitivity to actual alarms.

In accordance with another aspect of the present invention, a method and system for managing the generation of alarms for possible destabilizing events in a pipeline network is provided. The system preferably performs the method described herein. The method includes sensing one or more pressure waves within the pipeline network at predetermined locations within the pipeline network, automatically adjusting a predetermined stable operating threshold for the pipeline network at the predetermined locations based upon at least one of the operating mode of the pipeline network, current operating conditions in the pipeline network and current operating events in the pipeline network, and determining the presence of a possible destabilizing event in the pipeline network by determining whether or not the sensed pressure waves exceed the adjusted predetermined stable operating threshold. In response to the determination, the method further includes generating an alarm indicating the possible presence of a destabilizing event when the sensed pressure waves exceed the adjusted predetermined stable operating threshold. The determination of the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves may further include detecting variations in the sensed pressure waves, and determining whether or not the detected variation exceeds an accepted standard deviation. The accepted standard deviation may be an empirically determined standard deviation. The method may further include determining whether or not a subsequential decompression characteristic is present following the detection of a variation in sensed pressure waves. When the characteristic is present, an alarm is generated indicating the presence of a leak.

It is another aspect of the present invention to provide a monitoring system for detecting destabilizing events in a pipeline network and diagnosing the destabilizing events to identify (i) the location of the same and (ii) identify potential causes and remedial and/or corrective measures for the same. The system is especially useful in diagnosing both high level and lower level destabilizing events such that corrective measures can be implemented to minimize any long term detrimental impact on the pipeline network and to promptly return the network to stable operation.

In accordance with another aspect of the present invention, the a pipeline monitoring system is provided that diagnoses the potential source of destabilizing events. The system includes a control unit that diagnoses a potential cause of the sensed destabilizing event by comparing the character of the sensed destabilizing event using an expert based diagnostic subroutine with at least one of prior destabilizing events, the current operating mode of the pipeline network, the current operating conditions in the pipeline network and the current operating events in the pipeline network. The control unit may identify remedial measures to isolate or correct the possible destabilizing event in response to the determination that a possible destabilizing event exists. The control unit may then report the remedial measures to an operator of the pipeline network. It is also contemplated that the control unit may automatically execute the remedial measures.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other advantages of the present technique may become apparent upon reading the following detailed description and upon reference to the drawings wherein like reference numerals describe like elements and wherein:

FIG. 1 is an exemplary pipeline network in accordance with certain aspects of the present techniques;

FIG. 2 is an exemplary embodiment of the control center of FIG. 1 in accordance with aspects of the present techniques;

FIG. 3 is an exemplary embodiment of a pressure wave caused by a rupture in the pipeline network of FIG. 1.

FIG. 4 is an exemplary embodiment of a display shown to a pipeline operator in the control center of FIG. 1 in accordance with aspects of the present techniques;

FIG. 5 is an exemplary embodiment of one the logic flow in one of the aspects of the present techniques.

DETAILED DESCRIPTION OF THE INVENTION

In the following detailed description and example, the invention will be described in connection with its preferred embodiments. However, to the extent that the following description is specific to a particular embodiment or a particular use of the invention, this is intended to be illustrative only. Accordingly, the invention is not limited to the specific embodiments described below, but rather, the invention includes all alternatives, modifications, and equivalents falling within the true scope of the appended claims.

The present invention is directed to a system and method for detecting the occurrence of destabilizing events in one or more pipeline networks. The terminology “destabilizing event(s)” is intended to encompass any event or activity including but not limited to leaks, ruptures, equipment failures, equipment malfunction, process errors, etc that may have an adverse impact on the stable operation of the pipeline network. In particular, a real-time optimizer (RTO) is utilized with a Supervisory Control and Data Acquisition (SCADA) unit to detect destabilizing events in the pipeline by detecting pressure reactions within the pipeline, comparing these reactions with empirically determined acceptability for the current pipeline mode, eliminating those reactions caused by known pipeline events, using a method of sonar distancing to determine where the pressure reactions originated, and evaluating other real-time operational data to corroborate the occurrence of a rupture. The RTO is an expert algorithm based control system designed to optimize the safety and minimize the environmental impact of the pipeline due to destabilizing events while effectively managing the generation of alarm events. To enhance the detection of destabilizing events in pipelines, the RTO analyzes concurrent or real-time operational data from the SCADA unit. From the analysis, if a possible destabilizing event is detected, an alarm is generated via the SCADA unit to alert the operator of the pipeline network. The information used to assess the possibility of a rupture may be provided to the operator either graphically, audibly or textually or any combination thereof. It is contemplated that the system can recommend or automatically execute corrective measures to minimize the impact of destabilizing events on the pipeline system and return the pipeline network to stable operation.

Turning now to the drawings, and referring initially to FIG. 1, a pipeline network 100 in accordance with some aspects of the present techniques is illustrated. In the pipeline network 100, a fluid, such as one or more fluid commodities (e.g., oil, gas and products produced therefrom), is transported from a first facility 102 through various pipeline segments 104 and pump stations 106 a-106 n to at least a second facility 108. The first facility 102 and second facility may be any facility associated with the production, processing and transporting of oil, gas and/or products derived therefrom including but not limited to an oilfield production tree, surface facility, distribution facilities, oil sands plant or the like, an off-shore drilling platform, an off-shore distribution or transportation terminal, refineries, petrochemical facilities, etc. The pipeline segments 104 may include tubular members to transport of fluid commodities therethrough. It should be noted that n may be any integer number and that this embodiment is merely for exemplary purposes. For instance, other embodiments may include single or multiple product strip or injection points, branches in the pipeline, as well as any number of intermediate pump stations. The present invention is intended for use in various types of pipeline networks having one or more branches.

The pump stations 106 a-106 n includes one or more pumps 110 a-110 n, one or more sensors 112 a-112 n, and/or one or more meters 108 a-108 n. The pumps 110 a-110 n may include one or more synchronous electrical motor pumps, variable frequency drive (VFD) pumps and/or the like. The pressure sensors 112 a-112 n are preferably located both upstream of the first pump 110 a-110 n and downstream of the last pump 110 a-110 n in each pump station 106 a-106 n, as shown in FIG. 1 and FIG. 3. The meters 108 a-108 n are typically located only where the fluid commodities enter or leave the pipeline network 100, as shown in FIG. 1.

To manage and monitor the operation of the pipeline network 100, various processor based devices, such as remote monitoring devices 120, 121 and 122 a-122 n, are utilized to collect and communicate data about operational settings, which include equipment settings (e.g., equipment status, etc.) and measured parameters (e.g., pressure, temperature, flow rate, etc.) of the pipeline network 100. The remote devices 120, 121 and 122 a-122 n may be programmable logic controllers (PLCs), loop controllers, flow computers, remote terminal units (RTUs), human machine interfaces (HMIs), servers, databases and/or a combination of these types of processor based systems. These remote devices 120, 121 and 122 a-122 n may also include monitors, keyboards, pointing devices and other user interfaces for interacting with an operator.

Each of the remote devices 120, 121 and 122 a-122 n may be located in one or more of the first facility 102, pump stations 106 a-106 n, and second facility 108 to collect data from the sensors 112 the operational data, such as operational settings or telemetry data, from the equipment and/or meters 108 a-108 n associated with the pipeline network 100. The control signals from the equipment (e.g., pumps 110 a-110 n and/or meters 108 a-108 n) and sensors 112 a-112 n may be limited by the distance that the control signals may be transmitted by a switch or transducer that is part of the equipment or meter 108 a-108 n. As such, each of the remote devices 120, 121 and 122 a-122 n may operate as a central collection location for the data from one specific pump station 106 a-106 n or other pipeline facility. As an example, the operational settings may include data about the draw rate, pump status, drag reducer additive (DRA) injector status, valve status, DRA injection rate, variable frequency drive settings, flow rate in the pipeline segments 104, height of fluid within tanks in the facilities 102 and 108, fluid temperature; pressure in the pipeline segments 104, density of the fluid commodity, and/or batch interface. The remote devices 120, 121 and 122 a-122 n receive, process and store the various control signals in local memory. In this manner, the operational settings for each location may be efficiently managed thr further distribution to the control center 126.

The remote devices 120, 121 and 122 a-122 n interact with other devices that may be located at one or more control centers 126 via the network 124 to further process the operational data. The control centers 126 may include one or more facilities, which house various processor based devices having applications utilized to manage the equipment and monitor sensors 112 a-112 n or meters 108 a-108 n distributed along the pipeline network 100. A control center 126 is shown in greater detail below in FIG. 2. Because each of the remote devices 120, 121 and 122 a-122 n and the control centers 126 may be located in different geographic locations, such as different structures, cities, or countries, a network 124 provides communication paths between the remote devices 120, 121 and 122 a-122 n and the control centers 126. The network 124 may comprise different network devices (not shown), such as routers, switches, bridges, for example, may include one or more local area networks, wide area networks, server area networks, or metropolitan area networks, or combination of these different types of networks. The connectivity and use of the network 124 by the remote devices 120, 121 and 122 a-122 n and the devices within the control centers 126 is understood by those skilled in the art.

A control center 126 in accordance with aspects of the present invention is illustrated in FIG. 2. The control center 126 is utilized to monitor and control the equipment and sensors 112 a-112 n in the pipeline network 100. As a specific example of the operation performed by the control center 126, pseudo code is listed below in Appendix A. The control center 126 includes a supervisory control and data acquisition (SCADA) unit 202 coupled to various control devices 214 a-214 n via a network 212. The SCADA unit 202 provides a pipeline operator with access to operate the equipment in the pipeline network 100. While a single SCADA unit 202 is illustrated, it should be appreciated that the control center 126 may include one or more local or regional SCADA units and one or more master SCADA units to manage the local SCADA units in other control center architectures.

The SCADA unit 202 contains one or more modules or components that perform specific functions for managing the transport of the fluid commodities. For instance, the SCADA unit 202 may include a SCADA application 204 that includes one or more software programs, routines, sets of instructions and/or code to manage the operation of the pipeline network 100. The SCADA application 204 may include OASyS DNA by TELVENT; Ranger by ABB, Inc.; Intellution by GE, Inc.; and/or UCOS by Control Systems International (CSI), Inc, The SCADA unit 202 includes a data communication module 206 and a database 208. The data communication module 206 includes a set of instructions that manage communications with other devices (e.g., request the operational settings from the remote devices 120, 121 and 122 a-122 n at specific intervals or provide equipment settings to the devices 120, 121 and 122 a-122 n). The database 208 may be of any conventional type of computer readable storage device used for storing data, which may include hard disk drives, floppy disks, CD-ROMs and other optical media, magnetic tape, and the like, which stores the operational settings. The SCADA application 204 analyzes the operational settings, which may include converting the operational settings into a specific format for presentation to operators and/or identifying alarm conditions. The results of this analysis, along with the operational settings, are then stored in the database 208, as operational settings and operational reports. Then, the operational settings and operational reports may be synchronized to other databases of additional SCADA units in other locations.

In addition, the operational settings and operational reports may be presented to processor based devices, such as control devices 214 a-214 n, via the network 212 to provide an operator with data about the real-time operation of the pipeline network 100. The control devices 214 a-214 n may be computers, servers, databases and/or a combination of these types of processor based systems, which may also include display units (e.g. monitors or other visual displays), keyboards, pointing devices and other user interfaces for interacting with the operator. The network 212, which may include similar components to the network 124, may be utilized to provide communication paths between the control devices 214 a-214 n and the data communication module 206 in the SCADA unit 202. Typically, the network 212, which may include different networking devices (not shown), may include one or more local area networks or server area networks, but may also include wide area networks, metropolitan area networks, or combination of these different types of networks for certain operations. The connectivity and use of the network 212 by the control devices 214 a-214 n and the SCADA unit 202 is understood by those skilled in the art.

To operate the pipeline network 100, the operator enters operational instructions into one of the control devices 214 a-214 n. These operational instructions, which may include equipment settings or flow rates or operating modes (i.e., tight line mode or draw mode), for example, are communicated to the SCADA application 204 through the data communication module 206 in the SCADA unit 202. The SCADA unit 202 stores the operational instructions in the database 208 and may synchronize the operational instructions with other SCADA units. The SCADA application 204 analyzes the operational instructions and converts the operational instructions into equipment settings, which may be in the same or a different format that is accepted by the remote devices 120, 121 and 122 a-122 n. The SCADA application 204 converts the operational instructions from units of measurement for the operator into units of measurement for the remote devices 120, 121 and 122 a-122 n. The equipment settings are then transmitted to the remote devices 120, 121 and 122 a-122 n by the data communication module 206. Once received, the remote devices 120, 121 and 122 a-122 n acknowledge the equipment settings and transmit the equipment settings by providing the appropriate control signal to the equipment. The equipment settings (e.g. opening or closing flow control devices, starting or stopping pumps, and/or starting or stopping DRA injectors to adjust the rate DRA is being injected into the pipeline segments 104) are then executed by the respective equipment.

For the pipeline network 100 to operate efficiently, and carry a large volume of fluid from one facility 102 to another facility 108 the pumps 110 a-110 n are used to raise the pressure in the pipeline to pressure levels much greater than that of the atmosphere surrounding the pipeline segments 104 and pump stations 106 a-106 n. This pressure differential places stresses on the various elements of the pipeline network 100 used to contain the fluid being transported. As a consequence of these pressures, it is possible that the elements containing the pressure differential, and in particular compromised areas (corrosion) or lower rated pipeline elements, may rupture, as shown in FIG. 3, below. It is also possible that the pipeline equipment contained in the pumping stations and elsewhere may fail or operate improperly, which can create unstable operating conditions that may lead to a possible rupture. Furthermore, unstable operation could result from improper operational instructions entered into by one of the control devices 214 by the pipeline operator or the failure of the operator to adjust the necessary operational instructions in response to a change in operating mode or a change in the fluid within the pipeline.

When an element of the pipeline network 100 ruptures 300, the pressure at the rupture location rapidly changes, as the first molecules of fluid are pushed from the pipeline by the pressure differential. This pressure change causes pressure in the fluid adjacent to the rupture to change in response to the initial pressure change. This effect is carried through the pipeline network 100 as a pressure, shock or sound wave 301. The pressure wave 301 travels through the fluid at a speed relative to the sonic characteristics of the fluid or chain of batched fluids (gaseous or liquid) along the pipeline's length, so that the time the pressure wave 301 travels is mathematically relatable to the distance it has traveled. The operation of a pump 110 or other pipeline component may create a pressure or sound wave, which travels through the pipeline in a similar manner. The unstable operation of the pipeline may also create a pressure or sound wave within the pipeline. Such a wave may not be as high as those associated with a rupture.

Many of the prior art systems, some described above, designed to detect ruptures in the pipeline network typically do not use detection of a pressure wave in their analysis. These systems depend on a balancing algorithm to determine if fluid is leaving the pipeline at an un-metered location to determine if there is a rupture. As may be appreciated, these prior art systems require that a sufficient volume of fluid has left the pipe through the rupture before detection of the rupture can occur. This can result in a significant environmental impact in the area surrounding the rupture as inferential measurement systems are commonplace and relatively lethargic with respect to hydraulic wavespeeds and the ensuing segmental decompressions that follow rupture events in closed pressurized hydraulic networks. The systems that do sense acoustic waves described above only isolate ruptures and not other destabilizing events that impact the stable operation of the pipeline network.

To provide near real-time detection of a destabilizing event including a rupture 300, and thus allow more rapid and effective action, a real-time optimizer (RTO) 210 is utilized for analyzing operational settings within a SCADA unit 202. This enhances the operation of the pipeline network 100 in real-time to respond more effectively to destabilizing events.

The RTO 210 may be implemented as one or more software programs, routines, software packages, and/or computer readable instructions that interact with the SCADA unit 202, or specifically the SCADA application 204 and database 208. The RTO 210 may also be written in any suitable computer programming language. Through the RTO 210, additional functionality may be provided to the operator to provide reports and other notifications (whether visual or audible) of suspected pipeline destabilizing events including ruptures 300 through the detection and analysis of pressure waves 301. These notifications will allow the operator to respond to high level destabilizing events and lower level events that, if left ignored, could ultimately result in a high level destabilizing event including a rupture.

To obtain information regarding pressure waves for analysis, the RTO 210 requires the collection of additional information, which may be collected and processed by remote devices 120, 121, and 122 a-122 n. Unlike prior art systems with predetermined sampling at fixed intervals, the sampling for pressure waves occurs at the highest rate permitted by the pressure transmitter sensors 112. This significantly reduces the likelihood of a pressure wave going undetected. The electrical representation of the pressure reported by the pressure sensors 112 a-112 n to the remote devices 120, 121, and 122 a-122 n is typically measured and processed by the remote devices 120, 121, and 122 a-122 n at a high rate of speed (for example, every 50 milliseconds). This differs from existing pipelines, where previous values are typically discarded and values are transmitted to the control center 126 much less frequently, for example every ten seconds. As a result, the implementation of the system according to the present invention may require modification of the remote devices 120, 121, and 122 a-122 n to perform statistical calculations on the pressure values. Specifically, a standard deviation may be calculated for the pressure values collected during a short period of time (for example, 15 seconds). In accordance with the present invention, the calculated standard deviation is of a rolling nature. For example, the standard deviation is calculated using pressure values collected between times t1 and t5. The next standard deviation is calculated using pressure values collected between times t2 and t6. The next standard deviation is calculated using pressure values collected between times t3 and t7. All subsequent deviations are calculated in this rolling manner. By contrast, the prior art systems review their obtained acoustic information in fixed intervals (e.g., t1 to t5, t6-t10, t11-t15). With such a review, destabilizing events that start in one period and end in another period can be overlooked. The rolling calculation of the standard deviation in accordance with the present invention avoids this occurrence. The present invention is not intended to limited to the use of an empirically computed standard deviation; rather, numerous empirically based determinations (which are not based on force fit models) including but not limited to derivative function (1^(st), 2^(nd) and 3^(rd) derivatives), integral functions are well within the scope of the present invention.

An operational setting is established, such that the field devices 120, 121, and 122 a-122 n have available for their analysis a number representing a multiplier to be applied to the calculated standard deviation. Should the pressure sensors 112 a-112 n then report a pressure which exceeds the standard deviation calculated with the multiplier applied, the remote device 120, 121, and 122 a-122 n will declare the detection of a pressure wave 301. The normal hydraulic noise within pipeline systems produce a particular standard deviation character for the pipelines typical modes of operation white a destabilizing events such as loss of pipeline integrity (rupture) will produce a uniquely different standard deviation character than the family of normal mode standard deviation characters. Similarly, the startup or shutdown of a pump or an unstable operation of the pipeline will produce a uniquely different standard deviation character than the family of normal mode standard deviation characters.

In order to correlate pressure waves 301 between different pressure sensors 112 a-112 n, it is important to have an accurate measurement of time which is synchronized between all the remote devices 120, 121, and 122 a-122 n on the pipeline network 100. This is accomplished by providing a receiver and appropriate additional electronics within the remote device 120, 121, and 122 a-122 n to allow highly accurate time synchronizing updates to be collected from the transmissions of satellites used for Global Positioning Systems and provided to the logic unit of the remote device 120, 121, and 122 a-122 n.

As noted above, pressure waves 301 may be caused in the pipeline network 100 through other means which are considered part of normal pipeline operations, including but not limited to the starting and stopping of pumps 110 a-110 n and the opening and closing of valves. It is important that the pressure waves 301 caused by these events to be taken into consideration by adjusting the alarm triggering thresholds in real time or removing it from those being considered fir rupture detection. This may be done at the remote device 120, 121, and 122 a-122 n for those events that are initiated by the same remote device 120, 121, and 122 a-122 n that detected the pressure wave. Logic may be added to the remote device 120, 121, and 122 a-122 n to disable pressure wave detection for a certain period of time following an adjustment to an equipment setting that would result in a pressure wave. Alternatively, the triggering thresholds for a destabilizing event can be adjusted (i.e., raised or lowered) in response to the normal operating events such that destabilizing events may still be detected while accounting for the normal operating conditions. Superior possible methods include characterizing normal pipeline operating events under high speed trend analysis and build a comparative matrix of normal pipeline action characters and by reviewing these hydraulic signatures with empirically determined standard deviation thresholds providing an enhanced discrimination of destabilizing events from normal pipeline operating events and noise. This will provide an effective tool for managing the generation of alarms (i.e., false alarms) by the system,

As mentioned above, during normal operation of the pipeline network, various pressure waves are generated that are not attributable to a destabilizing event, but nonetheless create pressure activity that could generate an alarm signal. The control center 126 and remote devices 120, 121, 122 can factor in pressure waves attributed to normal pipeline operation. These waves can be discounted with the necessary adjustment to the alarm triggering thresholds to reduce the number of false alarms generated. Current monitoring systems generate thousands of alarms in a given day of pipeline operation. Many of these alarms are false, which result in operators either clearing or ignoring low level alarms. This not only reduces the amount of time an operator spends addressing each alarm, but also desensitizes the operator to respond to low level alarms. The discounting of pressure waves associated with known pipeline operations, their acceptable reactions, and the adjustment of the triggering thresholds thereto can be effectively reduced by at least 60% and more preferably by at least 80%. This represents a significant reduction in the generation of hydraulical alarms, which provides the operator with more time to respond to actual alarms and also respond to low level alarms indicating unstable operation before the unstable operation leads to higher level alarms and potential damage to the pipeline.

In order to provide the information regarding the detection of pressure waves to the RTO 210, the remote devices 120, 121, and 122 a-122 n interact with Data Communication Module 206, the SCADA Application 204 and into the database 208. From there the RTO 210 retrieves the data as needed by its algorithms.

Once a pressure wave report has been received, the RTO 210 waits a predetermined period of time for the particular instance of the pipeline network 100 for other pressure wave reports to be made available. The pressure wave from a destabilizing event may cause more than one pressure wave report, and having two or more reports is necessary to determine the location of the destabilizing event(s). The time period to wait is determined by dividing the length of the pipeline by the speed of sound in the fluid contained in the pipeline.

Pressure waves caused by normal operation of pipeline equipment are to be ignored by the RTO 210. These pressure waves are considered “Usual Suspects”, whether by reviewing the Usual Suspects hydraulic character for normalcy or by momentarily masking normal pipeline equipment actions from RTO2. To do this, the RTO 210 maintains a table listing the various normal, operational pipeline activities that cause a pressure waves 301 and stores within that table the time it would take a pressure wave 301 caused by that activity to reach each of the pressure sensors 112 a-112 m on the pipeline network 100. The RTO 210 must compare each of the pressure waves 301 reported by the pressure sensors 112 a-112 n with recent activity on the pipeline, removing them from consideration for destabilization event detection if the time of receipt indicates that they originated during a pipeline activity. Specific examples of the operation of the RTO 210 to identify and update Usual Suspects are illustrated as pseudo code under “Update Usual Suspects” and “Is a Usual Suspect” in Appendix A. The prior art systems compare the sensed wave to stored leak profiles. These systems, however, have limited capabilities because each leak may have a unique profile. As such each leak may not be identified. Unlike the prior art systems, the present invention compares pressure waves to normal operating conditions or normal operating events not predetermined leak profiles. As such, the present invention can more accurately detect an abnormal operating condition with greater accuracy.

Having assembled a list of pressure waves 301 that occurred during the period it would take such a wave to transit the pipeline, the RTO 210 must attempt to identify a bracketing pair of wave detections. That is, two wave detections from different pump stations 106 a-106 n, one on either side of the rupture 300. The rupture will be located between these two stations. This may be done by arranging the detections in chronological order, and then selecting the first two from unique stations 106 a-106 n while accounting for any sonic wavespeed character differences of fluids either side of the event on batched networks. The determination of whether this pair of detections is bracketing may then be determined using the following equation:

If (t ₂ −t ₁)≦t ₂₁

Then the pair is a bracketing pair

Where

-   -   t₂=time of the second detection     -   t₁=time of the first detection; and     -   t₂₁=time for a wave to travel from the station of the second         detection to the station of the first detection.         That is, if the time differential is not great enough for the         wave 301 to travel from one station 106 a-106 n to the other,         then the origination of the wave 300 must be between the         stations. Should the chosen pair not prove to be a bracketing         pair, then each additional pair must be examined in turn to         attempt to identify a bracketing pair.

The identification of a bracketing pair of wave detections provides a method to determine the location of the origin of the wave 300 (or suspected rupture). The following formula may be employed to make this determination:

d ₂=0.5*[d ₁₂+(t ₂ −t ₁)*ws]

where

-   -   d₂=distance from pump station 106 a-106 n where second detection         occurred towards pump station 106 a-106 n where first detection         occurred.     -   t₂=time of second detection     -   t₁=time of first detection     -   d₁₂=distance from pump station where second detection occurred         and pump station where first detection occurred.     -   ws=wave speed (speed of sound in fluid)

The detection of a pressure wave 301 not due to operational activity by two stations which are not bracketing cannot be used to determine the origin of the pressure wave 301, however, it still provides more location information than a single pressure wave detection. In this case, the RTO 210 can determine which side of a station 106 a-106 n the pressure wave 301 originated, by comparing the two times the pressure wave 301 was received. This can be accomplished in the following manner. If the pressure wave 301 is detected by a sensor located on a first side of the station 106 before it is detected on a corresponding sensor on an adjacent second side of the station 106, then the origin of the pressure wave is on the first side of the station 106. If the pressure wave 301 is detected by a sensor located on the second side of the station 106 before it is detected on the corresponding sensor on the first side of the station 106, then the origin of the pressure wave is on the second side of the station 106.

The RTO 210 also provides analysis on the trend of the pressures to corroborate the results of the pressure wave detection. One method to corroborate a destabilizing event leak along with the initial event signature detection is to compare the slope of the subject segment's nodal pressures from before the pressure wave 301 with the slope of the same nodal pressures from after the pressure wave 301. The slope of the pressure is calculated by the RTO 210 by storing a number of values of the pressure from predetermined and meaningfully brief time intervals. The slope is then determined by the following equation:

Slope=(latest pressure value−oldest pressure value)/(current time−oldest time)

The slope prior to the pressure wave 301 is compared with the slope after the pressure wave 301. If the slope has decreased by a value greater than that of a pre-configured parameter, the trend of the pressure has changed as a result of the pressure wave 301, and this information corroborates the possibility of a rupture 300 or other destabilizing event. Other mathematical or statistical approaches are usable (such as rate of change, sum of deltas, or combinations thereof).

The RIO 210, if metering is available, may also provide analysis on the trend of the net flow of fluid through the pipeline network 100 to corroborate the results of the pressure wave detection. The trend is determined by obtaining the measured flow rates from the meters 108 a-108 n at all entries and exits to the pipeline network 100 and summing them (in flow positive, out flow negative). A specific example of the operation performed by the RTO 210 is illustrated as pseudo code as “store line flow data” under “RTO Event Detection” in Appendix A. The results of this summation are then compared for before the pressure wave 301 and after the pressure wave 301. If the summation has increased by a value greater than that of a pre-configured parameter, the trend of the net flow has changed as a result of the pressure wave 301, and this information corroborates the possibility of a rupture 300 or other destabilizing event.

If the SCADA Application 204 is providing a line balance function, which is a traditional method of leak detection, done by comparing volume entering and leaving the pipeline network 100 with the volume in the pipeline network 100 then the RTO 210 can perform yet another corroboration. A typical line balance function will make available to the RTO 210 through the database 208, a value, known as the line balance divergence, representing the change in the imbalance of the line balance calculation over a short period of time, typically a few minutes. The RTO 210 provides analysis on the trend of the line balance divergence to corroborate the results of the pressure wave detection. The trend is determined by comparing the slope (or other mathematical or statistical comparison) of the line balance divergence over time from before the pressure wave 301 with the slope of the line balance divergence over time from after the pressure wave 301. The slope of the line balance divergence is calculated by the RTO 210 by storing a number of values of the line balance divergence for predetermined time intervals. Under the exemplary method, the slope is then determined by the following equation:

Slope=(latest line flow divergence value−oldest line flow divergence value)/(current time−oldest time)

A specific example of this operation of the RTO 210 is illustrated as pseudo code under “Get Line Flow Data” in Appendix A. The slope prior to the pressure wave 301 is compared with the slope after the pressure wave 301. If the slope has increased by a value greater than that of a pre-configured parameter, the trend of the line balance divergence has changed as a result of the pressure wave 301, and this information corroborates the possibility of a rupture 300. Beneficially, this corroboration will occur prior to the line balance function determining that there is a rupture 300. As multiple independent corroborating data permits a lower indicative line balance divergence to further support rupture likelihood.

The RTO 210, by placing data into the database 208, notifies the operator of the pipeline that a possible destabilizing event has occurred based on pressure wave detection and other corroborating evidence. This includes the creation of an incident report. A specific example of the operation performed by the RTO 210 is illustrated as pseudo code under “Create Incident Report” in Appendix A. The RIO 210 may report different levels of certainty to the operator based on the level of evidence available. An exemplary set of reporting levels is shown further in Table 1 below. Level 1 represents the highest level of certainty that a rupture 300 has occurred, while Level 4 represents a lower level of certainty. As the RTO 210 obtains further evidence the level being reported to the pipeline network 100 operator may change.

TABLE 1 Two Trigger Two Trigger Two Trigger Two Trigger Bracketed Bracketed One Trigger Same Station One Sided Spanned Not Spanned No Pressure No Line Flow No Line Level 4 Level 4 Level 4 Level 4 Level 2 Decay Divergence Balance Line Balance Level 4 Level 4 Level 4 Level 4 Level 2 Line Flow No Line Level 4 Level 4 Level 4 Level 4 Level 2 Divergence Balance Line Balance Level 4 Level 4 Level 4 Level 4 Level 2 Pressure No Line Flow No Line Level 2 Level 2 Level 2 Level 2 Level 1 Decay Divergence Balance Line Balance Level 2 Level 2 Level 2 Level 2 Level 1 Line Flow No Line Level 1 Level 1 Level 1 Level 1 Level 1 Divergence Balance Line Balance Level 1 Level 1 Level 1 Level 1 Level 1

FIG. 4 is an exemplary flow chart depicting the use of the RTO 210 in the pipeline network 100 with the SCADA unit 202. An operator of the SCADA unit 202 may utilize the RTO 210 to monitor the destabilizing event detection for the pipeline network 100, as described below.

The operation of the system in accordance with the present invention will now be described in connection with FIG. 4. The operation is initiated at step 402. A timer is then started in Step 404 to allow for later re-execution of the logic at short time intervals. The data collected, stored in database 208 and used for line flow trend analysis is updated at Step 406 to provide corroborating evidence for any possible destabilizing event detections. The data produced by the line balance functionality of the SCADA. Application 204 is then collected and analyzed in Step 408 for possible future use in corroborating destabilizing event detections. The current pressures are retrieved from the database 208 in Step 410, stored within the RTO 210 and analyzed for future use in corroborating destabilizing event detections. Any newly received pressure wave reports are evaluated in Step 412 against changes in measured parameters in the pipeline network 100 to determine whether or not the pressure wave report was caused by operational activity. If the wave report was caused by operational activity, it is removed from the list of pressure waves 300 to be analyzed by the RTO 210.

In Step 414 a determination is made whether or not the RTO 210 is waiting to receive additional pressure wave detection reports associated with a previously received report. The waiting time in Step 414 differs from the timer set in Step 404. The period is shorter. The waiting time in Step 414 is based upon the wave speed length. The waiting time is set based upon slowest possible wave speed. If a pressure wave is detected, then the waiting time will be based upon the time it would take to receive another pressure wave if such pressure wave had the slowest possible wave speed. If the determination is yes and the RTO 210 is waiting for associated reports, then the operation of the system proceeds to Step 416. If the determination is negative (i.e., no associated pressure reports are received) then the operation of the system proceeds to Step 426, which is discussed in greater detail below.

In Step 416, the counter associated with waiting for associated reports is decremented. This counter is then examined in Step 418 to determine if the waiting period has expired. If the waiting period has expired and an associated pressure wave report is received, then all of the received pressure wave reports will be processed in Step 420 to determine whether there are bracketing detections, or a single detection, the possible associated location and alarm level. In Step 422, a determination is made as to whether or not the analysis performed in Step 420 found a possible rupture. If a possible destabilizing event was found, the operation proceeds to Step 424 where an incident report is created, as shown in FIG. 5 and the corroborating factors examined to determine if corroboration has occurred. A notice and/or an automatic soft pipeline spooldown, or corrective measure algorithm is executed along with the incident report such that the operator of the system can take appropriate measures to isolate the leak and limit spills from the pipeline. The operation of the system then proceeds to Step 430 where the system waits until the timer activated in Step 404 expires. The operation then returns to Step 404 where the process is repeated. If no possible destabilizing event is identified, then the operation proceeds to Step 430 where the system waits until the tinier activated in Step 404 expires. The operation then returns to Step 404 where the process is repeated.

Returning to Step 414, if it is determined that the RTO 210 was not waiting for associated reports, then the operation of the system proceeds to Step 426 to determine if a new pressure wave detection has been received. If no pressure wave detection is received, the operation of the system proceeds to Step 430 where the system waits for the timer set in Step 404 to expire. The steps are then repeated with the setting of the timer in Step 404. If a new pressure wave detection is received in Step 426, the operation of the system proceeds to step 428 where the initialization of the data records for tracking the new pressure wave, the setting of a tinier to wait for associated pressure wave detections, and the saving of the pre-detection corroboration values for future analysis occurs. The operation of the system then proceeds to Step 430, where the system waits in the manner described above.

As discussed above in connection with Step 424, an incident report is created when a pressure wave reports indicates the occurrence of an event. The incident report may be presented via a graphical user interface to a display unit for the operator. An audible notification may also be provided. The graphical user interface may be a window provided to the operators via the SCADA unit 202, which includes graphical or textual data, a report or any other suitable data. An example of the graphical user interface is illustrated in FIG. 5.

The screen view is merely one example of an incident report that may be presented to an operator. As can be appreciated, additional operational settings and data may be presented in other embodiments.

The screen view in FIG. 5 is divided into various windows or sections. For instance, section 500 reports the date and time at which the first pressure wave detection occurred. Section 502 reports the current alarm level assigned to the pressure wave detection using the customizable alarm level matrix presented in Table 1, above. Because the alarm level assigned to the analysis of a possible destabilizing event detection may change over time, as more corroboration evaluation is completed, the date and time at which each level of alarm was reached is displayed in section 504. If a certain level of alarm was not reached for a particular detection, it is not displayed in this section.

Section 506 is used to track and report whether the investigation launched by the operator has been completed or not. If the analysis by the RTO 210 was able to determine a location (bracketing detections, or two detections on one side of the rupture) this is reported in section 508. Section 510 provides detailed information on the pressure wave detection(s) that were used to arrive at the location by the RTO 210 during its analysis. Section 512 reports the status of the pressure decay corroboration for the upstream station used in the detection, if it exists, whether it is still in progress, or if complete, whether corroboration was found or not. Section 514 reports the status of the pressure decay corroboration for the downstream station used in the detection, if it exists, whether it is still in progress, or if complete, whether corroboration was found or not. Section 516 reports the status of the line flow divergence corroboration, whether it is still in progress, or if complete, whether corroboration was found or not. Section 518 reports the status of the line balance divergence corroboration, whether it is still in progress, or if complete, whether corroboration was found or not.

As discussed above, the system in accordance with the present invention is effective in managing the generation of alarms in order to reduce the number of false alarms. In addition, it is contemplated that the present invention is useful in connection with diagnosing destabilizing events and recommending or automatically executing potential remedial measures. As discussed above, the system is useful in identifying the presence and location of both high level and lower level destabilization events. The control center 126 can evaluate the data which resulted in the generation of an alarm for a destabilizing event via an expert based pipeline diagnostic subroutine that considers the current destabilized character of the pipeline against the expert system's empirical knowledge of what the current mode's hydraulic character should look like while cross referencing all SCADA-known setpoint and equipment status against this preferred and expected character, the expert system could then automatically execute a corrective measure algorithm or, if preferable, issue a corrective measure notice to the human to address the low level alarm before the lower level destabilizing event escalates into a high level destabilizing event with potential catastrophic impact on the pipeline. It is also contemplated that the control center 126 can initiate a remedial or corrective measure to respond to destabilizing events to maintain stable operation.

It will be apparent to those skilled in subjects related to the art that various modifications and/or variations may be made without departing from the scope of the present invention. While the present invention has been described in the context of a pipeline, the present invention is not intended to be so limited; rather, it is contemplated that the present invention can be used in piping found in refining and petrochemical processing operations, upstream and exploration operations, and any other operation outside of the oil and gas field that is concerned with managing the stable operation of a pipeline and the fluids flowing therethrough. Thus, it is intended that the present invention covers the modifications and variations of the method herein, provided they come within the scope of the appended claims and their equivalents. 

What is claimed is:
 1. A method of real time dynamic monitoring a pipeline network to identify possible destabilizing events in the pipeline network, comprising: sensing one or more pressure waves within the pipeline network at predetermined locations within the pipeline network; determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves by detecting variations in the sensed pressure waves, and determining whether or not the detected variation exceeds an accepted standard deviation, wherein the accepted standard deviation is calculated on a rolling basis, wherein determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves further includes determining whether or not the sensed pressure waves exceed a predetermined stable operating threshold, wherein the predetermined stable operating threshold is automatically adjusted based upon at least one of the current operating mode, current operating conditions and current operating events, wherein determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves further includes determining whether or not a subsequential decompression characteristic is present following the detection of the variation in sensed pressure waves; and corroborating the presence of the destabilizing event; wherein corroborating the presence of the destabilizing event includes determining the certainty of the possible destabilizing event.
 2. The method according to claim 1, further comprising: issuing an alarm indicating the presence of a leak when it is determined that the subsequential decompression characteristic is present.
 3. The method of monitoring a pipeline network according to claim 1, further comprising: generating an alarm reporting the presence and certainty of the possible destabilizing event.
 4. The method according to claim 3, wherein the alarm has more than one alarm level, wherein the alarm level generated is based upon the determined certainty of the possible destabilizing event.
 5. The method according to claim 3, further comprising: managing the generation of alarms.
 6. The method of monitoring a pipeline network according to claim 1, further comprising: determining the location of the possible destabilizing event in the pipeline network in response to the sensed pressure waves.
 7. The method of monitoring a pipeline network according to claim 6, further comprising: generating an alarm reporting at least one of the presence and location of the possible destabilizing event.
 8. The method according to claim 8, wherein the alarm has more than one alarm level, wherein the alarm level generated is based upon the determined certainty of the possible destabilizing event.
 9. The method according to claim 1, further comprising: reporting the potential cause of the sensed destabilizing event.
 10. The method according to claim 9, further comprising: determining at least one corrective measure in response to the sensed destabilizing event; and performing at least one of reporting the at least one corrective measure to an operator of the pipeline network and automatically executing the at least one corrective measure.
 11. The method according to claim 1, further comprising: identifying a potential cause of the sensed destabilizing event by comparing the character of the current destabilizing events using an expert based diagnostic subroutine with prior destabilizing events, the current operating mode of the pipeline network, the current operating conditions in the pipeline network and the current operating events in the pipeline network.
 12. A method of real time dynamic monitoring a pipeline network to identify possible destabilizing events in the pipeline network, comprising: sensing one or more pressure waves within the pipeline network at predetermined locations within the pipeline network; determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves by determining whether or not the sensed pressure waves exceed a predetermined stable operating threshold, wherein the predetermined stable operating threshold is automatically adjusted based upon at least one of the current operating mode, current operating conditions and current operating events, wherein determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves further includes detecting variations in the sensed pressure waves, and determining whether or not the detected variation exceeds an accepted standard deviation, wherein the accepted standard deviation is calculated on a rolling basis, wherein the determining the presence of a possible destabilizing event in the pipeline network includes determining whether or not the sensed pressure waves exceed the adjusted predetermined stable operating threshold, wherein determining the presence of a possible destabilizing event in the pipeline network in response to the sensed pressure waves further includes determining whether or not a subsequential decompression characteristic is present following the detection of the variation in sensed pressure waves; determining the certainty of the possible destabilizing event; corroborating the presence of the destabilizing event based upon at least one of (i) one or more sensed pipeline network operating conditions and (ii) at least one independent process variable; and identifying a potential cause of the sensed destabilizing event by comparing the character of the current destabilized events using an expert based diagnostic subroutine with at least one of the prior destabilizing events, the current operating mode of the pipeline network, the current operating conditions in the pipeline network and the current operating events in the pipeline network.
 13. The method according to claim 12, further comprising: reporting the potential cause of the sensed destabilizing event.
 14. The method according to claim 13, further comprising: determining at least one corrective measure in response to the sensed destabilizing event; and one of reporting the at least one corrective measure to an operator of the pipeline network and automatically executing the at least one corrective measure.
 15. The method according to claim 12, further comprising: generating an alarm indicating the possible presence of a destabilizing event when the sensed pressure waves exceed the adjusted predetermined stable operating threshold, wherein the alarm has more than one alarm level, wherein the alarm level generated is based upon the determined certainty of the possible destabilizing event.
 16. The method according to claim 15, wherein generating an alarm indicating the possible presence of a destabilizing event further comprising generating an alarm indicating the possible presence of a destabilizing event when the sensed pressure waves exceed the adjusted predetermined stable operating threshold and the detected variation exceeds the accepted standard deviation.
 17. The method according to claim 15, wherein generating an alarm indicating the possible presence of a destabilizing event includes generating an alarm indicating the presence of a leak when it is determined that the subsequential decompression characteristic is present.
 18. The method according to claim 12, further comprising: generating an alarm reporting the presence and certainty of the possible destabilizing event.
 19. The method according to claim 18, wherein the alarm has more than one alarm level, wherein the alarm level generated is based upon the determined certainty of the possible destabilizing event.
 20. The method according to claim 17, further comprising: managing the generation of alarms.
 21. A dynamic system for monitoring a pipeline network, wherein the pipeline network having a first facility, a second facility, at least one pipeline segment connecting the first facility and the second facility such that the fluid can flow between the first facility and the second facility, and at least one pumping station connected to the at least one pipeline segment, whereby fluid flowing through the at least one pipeline segment flows through the at least one pumping station, the system comprising: a plurality of pressure sensing devices for sensing the presence of one or more pressure waves within the pipeline network; a plurality of remote monitoring devices operatively connected to the first facility, the second facility and the at least one pumping station, wherein the remote monitoring devices monitor the operation of the pipeline network and collect operating data of the pipeline network; and a control unit operatively connected to the plurality of pressure sensing devices and the plurality of remote monitoring devices for dynamic monitoring the operation of the pipeline network based upon signals received from the plurality of remote monitoring devices, wherein the control unit detects the presence of possible destabilizing events in the pipeline network by determining whether or not variations in the sensed pressure waves are present and whether or not the variation exceeds an accepted standard deviation, wherein the accepted standard deviation is calculated on a rolling basis, wherein the control unit further determines the presence of a possible destabilizing event by determining whether or not the sensed pressure waves exceed a predetermined stable operating threshold, wherein the control unit adjusts the predetermined stable operating threshold in response to at least one of the operating mode, current operating conditions and current operating events, wherein the control unit further diagnoses a potential cause of the sensed destabilizing event by comparing the character of the sensed destabilizing event using an expert based diagnostic subroutine with at least one of prior destabilizing events, the current operating mode of the pipeline network, the current operating conditions in the pipeline network and the current operating events in the pipeline network.
 22. The system for monitoring a pipeline network according to claim 21, wherein the control unit identifies remedial measures to isolate or correct the possible destabilizing event in response to the determination that a possible destabilizing event exists.
 23. The system according to claim 21, wherein the control unit performs at least one of reporting the remedial measures to an operator of the pipeline network and automatically executing the remedial measures.
 24. The system according to claim 21, wherein the control unit empirically determines the accepted standard deviation.
 25. The system according to claim 21, wherein the control unit comprising: a plurality of remote control units, wherein each of the plurality of remote control units being operatively connected to one of the plurality of remote monitoring devices, wherein each remote control unit detects the presence of possible destabilizing events sensed by the corresponding remote monitoring devices by determining whether or not variations in the sensed pressure waves are present and whether or not the variation exceeds an accepted standard deviation, wherein the remote control unit corroborates the presence of the destabilizing event based upon at least one of (i) one or more sensed pipeline network operating conditions and (ii) at least one independent process variable.
 26. The system according to claim 21, wherein the control unit further comprising: a master control unit operatively connected to each of the plurality of remote control units, wherein the master control unit further corroborates the presence of the destabilizing event from each of the remote control units based upon at least one of (i) one or more sensed pipeline network operating conditions and (ii) at least one independent process variable.
 27. A pipeline network for transporting fluids, comprising: a first facility; a second facility; at least one pipeline segment connecting the first facility and the second facility such that the fluid can flow between the first facility and the second facility; at least one pumping station connected to the at least one pipeline segment, whereby fluid flowing through the at least one pipeline segment flows through the at least one pumping station; and a monitoring system for monitoring the operation of the pipeline network, wherein the monitoring system comprising: a plurality of pressure sensing devices for sensing the presence of one or more pressure waves within the pipeline network; a plurality of remote monitoring devices operatively connected to the first facility, the second facility and the at least one pumping station, wherein the remote monitoring devices monitor the operation of the pipeline network and collect operating data of the pipeline network; and a control unit operatively connected to the plurality of pressure sensing devices and the plurality of remote monitoring devices for controlling the operation of the pipeline network based upon signals received from the plurality of remote monitoring devices, wherein the control unit determines (i) whether or not variations in the sensed pressure waves are present, and (ii) whether or not the variation exceeds an accepted standard deviation, wherein the accepted standard deviation is calculated on a rolling basis, wherein the control unit detects the presence of possible destabilizing events in the pipeline network in response to the sensed pressure waves based upon determining whether or not detected variations in the sensed pressure waves exceeds an accepted standard deviation, wherein the control unit determines the certainty of the possible destabilizing event.
 28. The pipeline network according to claim 27, wherein the control unit determines the location of a destabilizing event in the pipeline network based upon the location of the pressure sensing devices that sensed a pressure wave.
 29. The pipeline network according to claim 27, wherein the control unit identifies remedial measures to isolate or correct the possible destabilizing event in response to the determination that a possible destabilizing event exists.
 30. The pipeline network according to claim 27, wherein the control unit performs at least one of reporting the remedial measures to an operator of the pipeline network and automatically executing the remedial measures.
 31. The pipeline network according to claim 27, wherein the control unit comprising: a plurality of remote control units, wherein each of the plurality of remote control units being operatively connected to one of the plurality of remote monitoring devices, wherein each remote control unit detects the presence of possible destabilizing events sensed by the corresponding remote monitoring devices by determining whether or not variations in the sensed pressure waves are present and whether or not the variation exceeds an accepted standard deviation, wherein the remote control unit corroborates the presence of the destabilizing event based upon at least one of (i) one or more sensed pipeline network operating conditions and (ii) at least one independent process variable.
 32. The pipeline network according to claim 27, wherein the control unit further comprising: a master control unit operatively connected to each of the plurality of remote control units, wherein the master control unit further corroborates the presence of the destabilizing event from each of the remote control units based upon at least one of (i) one or more sensed pipeline network operating conditions and (ii) at least one independent process variable. 